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The purpose of this paper is to develop a meta-ranking of the world’s most innovative firms, which underscores the importance of external perceptions of innovativeness and of an innovation-based view on firm performance, including product, service, process, business model, management and organizational innovation.

This is an exploratory empirical paper, which integrates the results of five rankings of the world’s most innovative companies.

The five innovation rankings include a variety of companies based on different methods and strategic focus. This variety underscores the importance of a meta-ranking, whose multiple aggregation methods lead to consistent results. Only the following 11 companies are mentioned in at least three rankings, leading to a list of the 11 most innovative companies in the world: Amazon, Apple, Tencent, Google/Alphabet, Netflix, SpaceX, Tesla, Microsoft, IBM, Intel and General Electric. Overall, the meta-ranking is dominated by US companies from various industries with firms from China gaining importance.

The paper contributes to research into innovation antecedents and consequences by illustrating the importance of innovation perceptions. The meta-ranking highlights the need for pursuing different types of innovation, following the innovation-based view on firm performance with first-order and second-order innovations. Moreover, the results deepen our understanding of digital transformation and of capturing value from innovation in the digital economy because a considerable portion of the leading innovators has a business model emphasizing artificial intelligence and digital platforms, which have led to the generation of new and to the disruption of established markets.

The purpose of this paper is to observe how to invest in upper-middle income countries via an innovation perspective following global innovation index (GII) by multicriteria decision aid (MCDA) approach, once MCDA was designed to support subjective decisions.

Pearson’s correlation was the milestone for understanding innovation indicators at upper-middle income countries profiles. In a MCDA first step, the analytical hierarchy process (AHP) was applied to obtain the criteria weight. In this step, the judgments or evaluations inputted in AHP were collected from a sample composed by five experts in GII. After getting the criteria weights compose to GII, Borda and Preference Ranking Organization Method for Enrichment Evaluations (PROMÉTHÉE) methods were applied to obtain an MCDA-based GII. The inputs for this second step were: the weights come from AHP output; and the countries performance came from GII data.

As a result, it was found out the upper-middle countries’ rank to invest and groups with countries acting like “hubs” or “bridges” for economic sectors in near countries; when they are grouped according to their maximum and minimum scores profiles, observing not only a particular region but also similar profiles at diverse world areas.

Pearson-AHP-PROMÉTHÉE works as a supportive decision tool for several and complex investment perspectives from criteria and alternatives analysis regarding innovation indicators for upper-middle income countries. This combination also demonstrates grouping possibilities, aligning profiles and not only ranking countries for investment and eliminating others but also grouping countries with similar profiles via innovation indicators MCDA combined application.

Performed over a five-year time horizon, this paper aims to analyze the progression rates of technological innovation across 15 sub-provincial Chinese cities. The authors quantify and rate innovation performance, then rank the cities based on a purpose-built index designed to gauge the rate of technological progress.

Using the inferior constraint method, and a variety of national sources of data, the authors construct an innovation index based in part on new product sales revenue, proportion of college students, research and development expenditure of industrial enterprises in relation to gross industrial output value, contract deals in technical markets per capita, hazard-free treatment rate of waste, enterprises with technical development agencies accounts for industrial enterprises, number of high-tech enterprises and invention patent ownership per million population.

The findings provide a methodology for indexing cities, with 15 Chinese provincial cities as examples. Among the top five cities with the highest technological innovation index were Shenzhen, Nanjing, Guangzhou, Hangzhou and Wuhan. In the bottom were Shenyang, Changchun, Dalian, Xi’an and Harbin.

This study applied a new model of innovation at the city level for China. Application to other industries (real estate, manufacturing, etc.) and countries will extend boundaries of this model and show its wider applicability.

Companies can use this research and methodology when seeking new investments in high tech and innovative products. Locations offering more hospitable environments should be prioritized ceteris paribus.

One weakness of much of the international business and competitiveness literature is that it often views the country as the primary unit of analysis. In this way, nuanced views of the institutional environments within countries are often overlooked. This paper proposes a measure of regional rates of innovativeness across China.

Introduction: Today the ability of nations to develop and implement innovations is core for their international competitiveness. Ukraine is striving for innovation progress; however, its innovation performance is relatively low. The research problem is to find the bottlenecks, affecting Ukraine’s innovation capability.

Purpose: This study aims to research the national innovation capability profiles, based on cluster analysis, to develop an understanding of drivers and threats for the innovation capability of Ukraine.

Need of the study: The knowledge-based economy, which had already turned into one of the most efficient developmental models of the 21st century, became a key driver of international competitiveness for the leading developed countries due to their progressive structural shifts towards the growth of high-technology manufacturing and knowledge-intensive sectors. These trends are significant to capture for the sake of increasing the innovation capability of the economy of Ukraine.

Methodology: The study is based on the K-means clustering method, which is employed for identifying 10 country clusters based on the indicators of their R&D and innovation activities, which allowed us to assess the innovation capability of Ukraine in comparison with 140 countries of the world. Data selection and normalisation were based on the 2019 Global Competitiveness Report indicators.

Findings: The study showed that Ukraine’s innovation capability problems are typical for most developing countries and are prevalently connected to low R&D expenditures, patent applications, and international co-invention activities. Most countries, except for the technologically developed ones, follow the so-called ‘passive technological learning’ strategies, which usually result in low economic productivity.

Practical implications: Several innovation policy implications have been developed for the government of Ukraine based on the cluster analysis results and accounting for the problems of the national innovation system (NIS).

The purpose of this paper is to address the importance of cultural values, the organizational culture and management style for innovation. It also comparatively evaluates the actual performance of European countries in innovation.

In this paper, the theoretical frameworks of the well-known scholars Hofstede, House, Schwartz, Boisot and Cameron and Quinn are critically evaluated and compared with each other. In addition, the authors compared the cultural rankings and the actual performance in innovation of selected European countries. Before addressing the impact of culture on the innovative strength of nations, different definitions of innovation are being described. The theoretical framework developed on the basis of the six Hofstede dimensions is composed; the nine House dimensions are supplemented and the Schwartz values for innovative strength of nations are also being discussed. Culture as a knowledge asset, the positioning in information space and its influence on innovation following the theories of Boisot and the different cultural types as defined by Cameron and Quinn have been studied and evaluated. The performance of European countries in innovation has been evaluated on the basis of the Global Innovation Index, the patent applications to the European Patent Office and the European Innovation Scoreboard.

Based on literature review, one can conclude that there is a strong positive relation between several cultural characteristics of countries in question and their innovative strength. The results of this paper point out the importance of cultural values for innovation.

This research has assessed the relation between national culture in general on the innovative strength of nations. Future research on which cultural characteristics and management styles have the strongest correlation with the innovative strength of nations could provide valuable insights for both scholars in this research field and for institutions and companies that wish to improve their innovative strength.

The results of this study provide us with the insight that the innovative strength of a nation or organization can be altered by changing (parts of) its culture. A practical implication of this finding is that a government can, for example, increase its nation’s innovative strength by encouraging cooperation between different institutions and by limiting rules and regulations which could cause barriers in the innovation process.

A social implication of the findings of this study is the knowledge that to improve the innovative strength of a nation, a government needs to pursue a pro-active policy of transforming national culture, for example, by changing the educational system and decreasing the power distance between teachers and students. Such an effort to influence the national culture addresses interesting issues regarding the concept of social engineering.

By critically evaluating the qualitative cultural frameworks of several well-known scholars and relating them to quantitative statistical data about the innovative strength of nations, this study has combined the strengths of both qualitative and quantitative methodologies and produced non-trivial findings in an original manner.

Innovation output around the world is concentrated in very few economies possessing the requisite skills, knowledge and market acumen to capitalize on emerging technologies. Within the broader European Union, Central and Eastern Europe countries persistently lag in innovation rankings compared to their Western Europe counterparts. The existence of cultural barriers to innovation has been offered as an explanation for the lag, in the sense that perceptions about innovation affect innovation performance. The purpose of this paper is to provide evidence-based analysis on whether there are divergent perceptions at the firm level between East and West.

The focus is on four countries with distinct socioeconomic profiles (Germany, Poland, Portugal and North Macedonia) for which innovation data of sufficient granularity exist. Using Probit analysis across the regressors of firm size, sector and innovativeness, a detailed picture of perceptions of innovation emerges naturally.

The analysis demonstrates that there is no discernible East-West cultural divide but rather a palette of shades regarding perceptions of innovation, entrenched in firm-level characteristics. Specifically, firm size colors perceptions of innovation and such perceptions in turn are moderated by whether a firm is involved or not in innovation activities.

A better understanding of innovation culture at the firm level is essential to drive policy interventions aiming to remove barriers to innovation. The results of this study provide sufficient clues for more refined interventions, both internal (“procedures”) and external (“policies”) to the firm, targeting well-defined size segments as well as addressing differently innovative and non-innovative companies.

The purpose of this study is to investigate the factors that influence the innovation decisions of Emirati women-owned small and medium-sized enterprises (SMEs).

This study uses a two-phased approach. In the first phase, empirical research on 50 Emirati female entrepreneurs is conducted to discover the extent of innovation in their ventures. In the second phase, the study uses an analytical hierarchy process (AHP) to prioritize factors considered important in facilitating business innovation among SMEs. The AHP model is developed with 9 criteria and 25 sub-criteria based on the previous literature. Face-to-face interviews are conducted with Emirati female entrepreneurs operating nascent (n = 10), start-up (n = 10) and established innovative (n = 10) businesses to collect data for the AHP study. The data collected are interpreted and a priority vector is assigned to each criterion and sub-criterion.

Female SME owners prioritize government policies, research and development, innovation strategy and skill development as the main criteria that influence their innovation decisions. Family support, access to external financing, social networks and the allocation of funds are the main sub-criteria affecting their decisions to be innovative. Furthermore, respondents who are in the nascent business stage consider family motivation as the greatest influence on initiating new ideas through financial and moral support. Among all respondents, the nascent business owners rank skill development the highest because they are still in the initial stages of their business journeys, and thus, obtaining these skills could help them increase innovation and success in their ventures. However, respondents in the established stage rank innovation strategy the highest.

The study results can help policymakers and women’s associations, such as businesswomen councils, identify the specific inhibitors and facilitators linked to innovation and, thereby, help develop various effective policies to promote innovation among Emirati women-owned SMEs.

The study is one attempt to facilitate innovation among Emirati women-owned SMEs through its efforts to discover the determinants of innovation efforts at nascent, start-up and established business stages as defined by the Global Entrepreneurship Monitor (2012). The study can help Emirati women-owned SMEs understand the critical factors influencing innovation and can encourage them to incorporate innovative characteristics for business growth and resilience. Furthermore, the study can provide insights for policymakers, financial institutions and non-governmental organizations on factors hindering innovation among Emirati women-owned SMEs, which may serve as a tool for creating resilience among female entrepreneurs.

The European Innovation Scoreboard is an important indicator of innovation performance across European Member States. Despite its wide application, the indicator fails to highlight the interlinkages that exist among innovation measures and focuses primarily on the linear relationship between the individual measures and the predicted outcome. This study aims to address this gap by applying a novel technique, the fuzzy-set qualitative comparative analysis (fsQCA), to shed light on these interlinkages and highlight the complexity of the determinants underlying innovation performance.

The authors adopted a configurational approach based on fsQCA that is implemented on innovation performance data from European Member States for the period 2011–2018. The approach is based on non-linearity and allows for the analysis of interlinkages based on equifinality, that is, the model recognises that there are different potential paths of high and low innovation performance. In addition, the approach allows for asymmetric relations, where a low innovation outcome is not the exact inverse of that which leads to high innovation outcome.

The results clearly indicate that innovation outcomes are not based on simple linear relations. Thus, to reap the desired effects from investments in innovation inputs, the complex set of indicators on which innovation performance is based should be taken into consideration. The results clearly indicate the elements of equifinality and asymmetric relations. Different paths lead to high innovation performance and low innovation performance.

The method applied to investigate the determinants of innovation performance is the prime original factor of this study. Thus, the study contributes to literature by highlighting the complexity involved in understanding innovation. By recognising and attempting to detangle this complexity, this study will assist not just academics but also policymakers in designing the necessary measures required to reach this important outcome for a country’s competitive edge.

Many cities across the world are actively investing in ways to excel in the innovation economy through the development of innovation districts as one of the most popular policy options. While innovation districts are among the leading drivers of innovation activities in cities, they are also high-cost and high-risk investments. Besides, holistic approaches for assessing these districts’ multifaceted performances are scarce. Bridging this knowledge gap is critical, hence, this paper aims to explore how innovation district performance can be assessed through a classification framework.

The paper introduces a multidimensional innovation district classification framework and applies it into Australian innovation districts with divergent features, functions, spatial and contextual characteristics. The study places 30 innovation districts from South East Queensland under the microscope of the framework to assess the multifaceted nature of innovation district performance. It uses qualitative analysis method to analyse both the primary and secondary data, and descriptive analysis with basic excel spreadsheet calculations to analyse the validity of the data.

The data analysis clusters 30 innovation districts from South East Queensland under three performance levels – i.e. desired, acceptable and unsavoury – concerning their form, feature and function characteristics.

The results disclose that the framework is a practical tool for informing planners, developers and managers on innovation district performances, and it has the capability to provide guidance for policymakers on their policy and investment decisions regarding the most suitable innovation district types and characteristics to consider.

This paper aims to analyse whether and how the Development Plan and Policies of Slovenian Tourism (SiPlan) could be improved systematically and systemically, enabling more comprehensive management of innovation.

The data were obtained within a comprehensive national innovation study. Data analysis was performed in four phases. In the initial phase, a link between the innovation project and SiPlan was established. In the next phase, which of the innovation factors are significantly correlated with the tourism destination development concept was identified. In the third phase, further policy potential for improving the innovation factors was identified. In the last phase, a systems approach was applied to develop a qualitative systems model, a causal loop diagram, taking into consideration the empirically identified strengths and weaknesses of the current SiPlan and other pertinent factors.

The results of empirical research indicate that SiPlan represents a valuable, but not optimum development model of Slovene tourism development. Therefore, the authors propose a qualitative tourism development model based on the research results and a systems dynamics methodology.

The work is important from the scientific point of view, i.e. as a methodology and research results that could be applied in further research activities. In addition, the results could be usefully used by policy makers by way of focusing on the most influential factors: policies that have a potential for the systems (holistic) and socially responsible development of tourism in Slovenia.